The subject matter disclosed herein relates generally to systems and methods for noise reduction, and more particularly to systems and methods for multichannel noise reduction.
In diagnostic imaging systems, good image quality is desirable, such as to provide images with clinically relevant information. For example in a x-ray system, data may be processed to reduce noise, thereby improving image quality. This improvement in image quality is typically achieved by reducing the discrepancy between a true attenuation value and the measured value. In a Computed Tomography (CT) system, for a basic reconstruction, approximately 1000 projections are used, where a single projection contains over 1000 measurements within a single x-ray spectrum. Thus, the noise in multichannel imaging systems is even more complex as noise is contributed by each channel. Moreover, the noise is not localized when multiple x-ray spectra are utilized for collecting the projection data.
In conventional systems using multichannel signals, in order to reduce noise it is important to preserve a signal characteristic in the multichannel signals where the signal characteristic exists in one channel signal and may be absent in another signal channel. Using conventional noise reduction methods, these differences introduce artifacts. Additionally, conventional noise reduction methods contaminate the channel signal, particularly the signal which lacks the signal characteristic being preserved.